Abstract: The disclosure generally relates to systems and methods for detecting personally identifiable information (PII). The present systems and methods solve the problem of detecting the PII and the PII column names in the customer database with enhanced accuracy, by developing a PII classification model trained with an enhanced and effective training dataset. An enhanced sub-metadata from the metadata having the plurality of the column names is obtained by using highest match distance values, the string comparator values, and the is PII indicator values. The enhanced sub-metadata comprising the column names that can be easily differentiated as PII columns or non-PII columns. Hence the training dataset and the testing dataset obtained from the enhanced sub-metadata improves the accuracy of the PII classification model. Preventive measures can be taken to protect such detected PII present under the PII columns by employing various data privacy and protection techniques.

Abstract: Existing systems provide data selection for one differential technique considering an analytical problem or synthetic data but not an arrangement for selection of one or more techniques together. The embodiments herein provide a method and system for differential privacy enabled service with hybrid rule management and similarity metrics to select data. The system generates a query table called universal data from the associates tables and databases. The system further based on query on the universal table of single columns or selected columns with different parameters using different privacy rules generates differential private data stored in temp tables/views. The system retrieves queried data of different techniques and parameters interactively viewing the privacy and similarity of each data types of retrieved data with universal data using different metrics like bar charts, Histograms, average, std.

Abstract: This disclosure relates generally to a system and method for masking text within images. Conventionally, image masking approaches have enabled masking but masking PII data which contains sensitive data is still a challenge. The present disclosure includes training and masking phase, wherein during training phase the PII label and values of the input image are captured and stored as co-ordinates in the database. During masking, the test image and the words comprised in the test image are optimized using an OCR technique. The label and value of each pairs are compared with the words comprised in the optimized test image. The comparison results in one or more matching labels and then a masking area is calculated for each matching label. The masking string is generated for each matching label based on the calculated masking area and the original text is masked with the generated string.

Abstract: The disclosure generally relates to systems and methods for detecting personally identifiable information (PII). The present systems and methods solve the problem of detecting the PII and the PII column names in the customer database with enhanced accuracy, by developing a PII classification model trained with an enhanced and effective training dataset. An enhanced sub-metadata from the metadata having the plurality of the column names is obtained by using highest match distance values, the string comparator values, and the is PII indicator values. The enhanced sub-metadata comprising the column names that can be easily differentiated as PII columns or non-PII columns. Hence the training dataset and the testing dataset obtained from the enhanced sub-metadata improves the accuracy of the PII classification model. Preventive measures can be taken to protect such detected PII present under the PII columns by employing various data privacy and protection techniques.

Abstract: This disclosure relates generally to a system and method for masking text within images. Conventionally, image masking approaches have enabled masking but masking PI data which contains sensitive data is still a challenge. The present disclosure includes training and masking phase, wherein during training phase the PI label and values of the input image are captured and stored as co-ordinates in the database. During masking, the test image and the words comprised in the test image are optimized using an OCR technique. The label and value of each pairs are compared with the words comprised in the optimized test image. The comparison results in one or more matching labels and then a masking area is calculated for each matching label. The masking string is generated for each matching label based on the calculated masking area and the original text is masked with the generated string.

Abstract: Methods and systems for masking data columns in a database are described herein. The method describes obtaining a masking template. Further the method describes associating the masking template with at least one rule and selecting columns based on the at least one rule. The method further describes identifying at least one column from the selected columns for applying masking setup and initiating masking setup on the at least one column based on the masking template.

Abstract: The present subject matter relates a testing system for an application. The system includes a test data generation module to generate test data for a program code. The test data generation module in turn includes a relational expression creation module that determines a relational expression corresponding to a set of parameters of the program code based on a rule indicating a format of a valid test data for the parameters. A boundary recognition module identifies a set of boundary values of the parameters based on the relational expression. Further, a solver module then generates valid test data and invalid test data for the parameters based on the boundary values.

Abstract: The present subject matter relates to systems and methods for database sampling. The method comprises identifying at least one query table and one or more associated tables amongst a plurality of tables in a production database, based on filtering criteria. Further, the method comprises generating a key value list for the at least one query table and each of the one or more associated tables based on an order indicated by an order list. Based on the generated key value list, the sample data is extracted in a reverse order indicated by the order list, from the at least one query table and each of the one or more associated tables.

Abstract: A method and a system for administering pay-per-use (PPU) licensing of software applications are disclosed. The system comprises a processor and a memory. The memory comprises an administrative module configured to generate a license file based upon a request sent by a user. The license file is used by the user for accessing a software application. The administrative module is further configured to receive a log file from the user. The log file comprises a track of at least one of a number of usages of the software application and a time period of the software application. The memory further includes an assessment module configured to determine a validity of the license file based upon the log file.

Abstract: Methods and systems for masking data columns in a database are described herein. The method describes obtaining a masking template. Further the method describes associating the masking template with at least one rule and selecting columns based on the at least one rule. The method further describes identifying at least one column from the selected columns for applying masking setup and initiating masking setup on the at least one column based on the masking template.

Abstract: The present subject matter relates to systems and methods for database sampling. The method comprises identifying at least one query table and one or more associated tables amongst a plurality of tables in a production database, based on filtering criteria. Further, the method comprises generating a key value list for the at least one query table and each of the one or more associated tables based on an order indicated by an order list. Based on the generated key value list, the sample data is extracted in a reverse order indicated by the order list, from the at least one query table and each of the one or more associated tables.

Abstract: The present subject matter relates a testing system for an application. The system includes a test data generation module to generate test data for a program code. The test data generation module in turn includes a relational expression creation module that determines a relational expression corresponding to a set of parameters of the program code based on a rule indicating a format of a valid test data for the parameters. A boundary recognition module identifies a set of boundary values of the parameters based on the relational expression. Further, a solver module then generates valid test data and invalid test data for the parameters based on the boundary values.